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Paper Information

Journal:   JOURNAL OF THE EARTH AND SPACE PHYSICS   fall 2018 , Volume 44 , Number 3 ; Page(s) 641 To 658.
 
Paper: 

Avalanche potential forecast using a numerical weather predicton model, (Case study: Shahrestanak zone, 26-28 December 2016)

 
 
Author(s):  TAJBAKHSH S.*, NIKFAL A.H.
 
* Atmospheric Survey Research Group, Atmospheric Science and Meteorological Research Center, ASMERC, Tehran, Iran
 
Abstract: 
Avalanches are likely to happen in winter time mountainous regions of Iran, and its timely prediction can help to improve the road traffic safety. The aim of this study is to provide the avalanche first guess using Numerical Weather Prediction (NWP) model outputs. Since the meteorological observations in mountainous areas are very scarce, access to snow data in ground measurements is not feasible; it seems that making use of numerical models to simulate the associated data and predicting the avalanche first guess may be a reliable method. For this purpose, three avalanche events which occurred in Chalous Road (Kanduan-Gachsar) were investigated synoptically as the case studies. Then the precipitation (water equivalent to snow, snow thickness), temperature and wind outputs of Weather Research and Forecasting (WRF) model were analysed based on the Spangler classification tables in order to determine the potential of avalanche events. Snow density, snow water equivalent and snow depth are the most important factors of snow cover that have fundamental applications in predicting avalanche and flood events. The predictions in this study are based on the WRF model numerical simulations. Spangler et al. (2009) presented a model for estimating the avalanche potential based on the three components of the region’ s climatic conditions, present weather survey and forecasting avalanche indices. For verification of the model, the threshold values for precipitation, temperature and wind were calculated in Colorado. In the present study, only the third part of the Spengler method (prediction of avalanche occurrence potential) was applied to make the first guess of avalanche potential occurrence in the mountainous regions of the country. The period 26-29 December 2016 for heavy snow conditions with multiple avalanche was considered as a case study. The area under study is the Shahrestanak (36, 10 ° N and 51. 31° E) on the Chalous road, which experienced more than 10 avalanche events during winter 2016. Its elevation is about 2230 to 2240 meters and is located in Alborz Province. There are similar climatic conditions in the two regions of Colorado and Alborz based on the Gutten climate classification but their temperature and type of snowpack are different according to the Sturm snowpack classification. The type of snowpack in the Colorado area is prairie (thin and moderate cold snow covering with substantial wind drifting, with the maximum depth of about 1 meter), while the type of snowpack in Alborz area is ephemeral (thin and warm snow that melts down soon and its depth is between zero to 50 cm). Hence, it seems that the thresholds of the meteorological indicators related to avalanche potential in Alborz region could be slightly lower than its thresholds in Colorado area. The synoptic study was done using the mean daily ERA-Intrim data. In the present study, the patterns of sea level pressure, thickness of 500/1000 hPa, geopotential heights and temperature with relative vorticity of 500 hPa, vertical velocity at 700 hPa, as well as relative humidity and winds of 850 hPa were studied in order to identify the weather conditions during the avalanche period. Also, using the WRF meso-scale model (ver. 3. 9), the simulation of atmospheric condition is conducted for 4 days (26-29 December 2016). Temperature, wind, cloudiness, snow thickness, snow water equivalent and snow cover (the most important indicators of avalanche) were determined using the WRF numerical prediction model. Then the potential of avalanches’ occurrence was investigated according to the Spengler model. Here, we attempt to investigate the potential of avalanche event in a case study using a NWP model and determine the probability of occurrence of avalanche based on one of the existing methods. The case study was selected in such a way that no significant atmospheric conditions were observed in the area. There was only one case of avalanche over 24 hours in the Chalous Road, Shahrestanak position. The results showed that the patterns of weather forecasting in this study are in agreement with actual weather conditions and there is no specific feature for avalanche occurrence in these patterns. The presented thresholds for the avalanche potential have good match in this case study. Winds of less than 9 m/s, snow depth of less than 30 cm in 24 hours, temperature of less than 8 ° C in 12 hours, unstable temperature in the range of-4 to-10° C, and cloudy sky during the day without rain emphasize the probability of avalanche and not its certainty. To predict the high potential for avalanche, the atmospheric thresholds should be higher than these values.
 
Keyword(s): Snowpack,Snow depth,Snow water equivalent,Avalanche,WRF numerical weather prediction
 
 
References: 
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Cite:
APA: Copy

TAJBAKHSH, S., & NIKFAL, A. (2018). Avalanche potential forecast using a numerical weather predicton model, (Case study: Shahrestanak zone, 26-28 December 2016). JOURNAL OF THE EARTH AND SPACE PHYSICS, 44(3 ), 641-658. https://www.sid.ir/en/journal/ViewPaper.aspx?id=653842



Vancouver: Copy

TAJBAKHSH S., NIKFAL A.H.. Avalanche potential forecast using a numerical weather predicton model, (Case study: Shahrestanak zone, 26-28 December 2016). JOURNAL OF THE EARTH AND SPACE PHYSICS. 2018 [cited 2021April19];44(3 ):641-658. Available from: https://www.sid.ir/en/journal/ViewPaper.aspx?id=653842



IEEE: Copy

TAJBAKHSH, S., NIKFAL, A., 2018. Avalanche potential forecast using a numerical weather predicton model, (Case study: Shahrestanak zone, 26-28 December 2016). JOURNAL OF THE EARTH AND SPACE PHYSICS, [online] 44(3 ), pp.641-658. Available: <https://www.sid.ir/en/journal/ViewPaper.aspx?id=653842>.



 
 
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